style_transfer | Data-parallel image stylization using Caffe | Machine Learning library

by crowsonkb Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | style_transfer Summary

style_transfer is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. style_transfer has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Data-parallel image stylization using Caffe. Implements A Neural Algorithm of Artistic Style [1]. The current preferred Python distribution for style_transfer is Anaconda (Python 3.6+ version). style_transfer will run faster with Anaconda than with other Python distributions due to its inclusion of the MKL BLAS (mathematics) library. In addition, if you are running Caffe without a GPU, style_transfer will run a great deal faster if compiled with MKL (BLAS := mkl in Makefile.config). Cloud computing images are available with style_transfer and its dependencies preinstalled. Command line arguments are documented in detail in the work-in-progress parameter usage guide.

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Support

style_transfer has a low active ecosystem.

It has 106 star(s) with 15 fork(s). There are 13 watchers for this library.

It had no major release in the last 6 months.

There are 10 open issues and 13 have been closed. On average issues are closed in 11 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of style_transfer is current.

Quality

style_transfer has 0 bugs and 0 code smells.

Security

style_transfer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

style_transfer code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

style_transfer is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

style_transfer releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

style_transfer saves you 719 person hours of effort in developing the same functionality from scratch.

It has 1661 lines of code, 112 functions and 12 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed style_transfer and discovered the below as its top functions. This is intended to give you an instant insight into style_transfer implemented functionality, and help decide if they suit your requirements.

Run tile worker
Evaluate features of a feature tile
Setup exceptions
Configure a logger
Process one request
Compute the loss and gradient of the model
Variant of V - norm
Compute p - norm
Rolls an array along a given axis
Multiscale layers
Transfer images
Resize image
Convert image to image
Parse command line arguments
Evaluate the config file
Setup sys excepthook
Return a list of GPU devices
Return a comment for image
Resize the parameters
Dump the experiment to a csv file
Roll the gradient
Calculate the weighted normalization of the wavelet transform
Setup a logger
Print the arguments to stdout
Start the event loop
Calculate the curvature pair
Create message type based on fields

Get all kandi verified functions for this library.

style_transfer Key Features

No Key Features are available at this moment for style_transfer.

style_transfer Examples and Code Snippets

No Code Snippets are available at this moment for style_transfer.

Community Discussions

Trending Discussions on style_transfer

python: A problem of image i/o based on fastapi

How to use Tensorflow Hub Model?

How does TensorFlow compute the gradient of vgg19.preprocess_input?

is there any way to deploy custom ML models in flutter?

QUESTION

python: A problem of image i/o based on fastapi

Asked 2022-Mar-22 at 19:27

I try to make a code for image style transfer based on fastapi.

I made the code by referring to many articles in Github and stack overflow, I found it effective to convert the byte of the image into base64 and transmit it.

So, I designed my client code was encoded into base64 and sent a request, and my server received it perfectly.

However, I faced difficulties in restoring image bytes to ndarray.

My code tells me the following this errors:

...

ANSWER

Answered 2022-Mar-22 at 19:27

As previously mentioned here, as well as here, one should use UploadFile to receive file data from clients. For example:

server side

Source https://stackoverflow.com/questions/70710874

QUESTION

How to use Tensorflow Hub Model?

Asked 2021-May-26 at 14:06

GOAL to use a pre trained model from a TensorFlow example project more specifically Tensorflow hub

To do that am trying to install tensorflow_hub with the following command: conda install -c conda-forge tensorflow-hub
conda list OUTPUT: .... tensorflow-hub 0.12.0 pyhca92ed8_0 conda-forge ....
To a sagemenaker EC2 instance's anaconda environment.
The whole installation process runs thru without any error, but when I am trying to import the package it act like it is not installed import tensorflow_hub as hub
ERROR

...

ANSWER

Answered 2021-May-26 at 14:06

I just installed from the Jupiter notebook
pip install --upgrade tensorflow_hub
this did not overwrite all the other files somehow.
The base environment was a SageMaker conda_tensorflow2_p36
you can activate it as conda activate tensorflow2_p36

Source https://stackoverflow.com/questions/67693198

QUESTION

How does TensorFlow compute the gradient of vgg19.preprocess_input?

Asked 2020-Oct-09 at 01:08

I am following the tutorial on neural style transfer. The style transfer is done by minimizing a loss function with respect to an image (initialized with the content image). What confuses me is the following piece of code:

...

ANSWER

Answered 2020-Oct-09 at 00:55

This has nothing to do with the model or gradients. What this function does is scale the input images so the pixels are in the range from -1 to +1. This is a common requirement for many models used in transfer learning like VGG and MobileNet. If you use the ImageDataGenerator it has a parameter preprocessing_function which the generator calls to preprocess the images. Make sure if you preprocess the training images you do the same for the test and validation images.

Source https://stackoverflow.com/questions/64272059

QUESTION

is there any way to deploy custom ML models in flutter?

Asked 2020-Jun-22 at 03:29

I am trying to create a flutter app using the ML model from the below link.

https://www.tensorflow.org/lite/models/style_transfer/overview

...

ANSWER

Answered 2020-Jun-21 at 18:51

You can upload custom tensorwflow model to firebase ML KIT (custom tab), and integrate with firebase API in your flutter project.

Source https://stackoverflow.com/questions/62502847

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install style_transfer

You can download it from GitHub.
You can use style_transfer like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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